Examining the Linkages between GDP Growth and … the Linkages between GDP Growth and Sustainable...

EAST-WEST Journal of ECONOMICS AND BUSINESS

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Journal of Economics and Business Vol. XVII – 2014, No 2

Examining the Linkages between GDP Growth

and Sustainable Development in the Eurozone

Ioannis A. Tampakoudis1, Dimitra Fylantzopoulou

2 & Konstantina

Nikandrou3

ABSTRACT: The paper intends to investigate the link between sustainable

development and GDP growth rate in the Eurozone. We utilize a defined set of

eleven indicators of sustainability according to the European Commission,

performing an econometric analysis focusing both on the Eurozone and on each

country separately. Among others, “Employment rate of older workers”,

“Resource productivity”, “Real GDP”, “Energy consumption by transport

mode”, “Gas emissions” and “Total renewable electricity net generation” seem

to be the indicators with the highest importance. However, the last three

sustainable indicators are unfavorably connected with GDP growth rate,

indicating the necessity for alterations on the current economic model. Apart

from a general strategic plan that is required in the EU context, certain policies

should be applied in each country due to distinctive characteristics in the social,

economic and political levels. Particularly for those countries experiencing the

current financial crisis, the idea of sustainable development constitutes an

exceptional opportunity that could lead to significant economic achievements.

KEYWORDS: Sustainable development; Eurozone; Indicators; European

Commission; GDP growth; Action plan.

1Department of Business Administration, University of Macedonia, e-mail: [email protected]. 2Department of Economics, University of Macedonia, e-mail: [email protected]. 3 Department of Economics, University of Macedonia, e-mail:[email protected].


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JEL Classification: Q3, Q4

Introductory observations and the paper objectives

During the last decades, mankind has achieved considerable developments that

have led to dramatically improved standards of living. Apart from the developed

countries of the West, the developing and emerging economies have shown

remarkable progress reflected in high levels of GDP growth rates. However, in

that pace of ongoing growth, the natural resources were used thoughtlessly,

while the legal framework and implementation of environmental issues were

quite lax. Conventionally, wisdom in politics asserts that economic growth and

environmental protection are conflicting concepts, composing a subject of

controversy. In fact, many believe that an increase of economic activity

inevitably evokes the degradation of the environment, which in turn could lead to

a possible economic as well as ecological collapse. This conflict that inevitably

affects the existing social and economic organization can be viewed as a

reflection of the lack of robust empirical evidence regarding the impact of

growing income levels on environmental quality. At that point, human needs

required a new notion which would be able to merge economic growth and

environmental issues; thus, the concept of sustainable development highly

reflects the coexistence of environmental quality, economic growth and social

prosperity.

The first steps towards an alternative growth model aligned with the rhetoric of

natural resources and limited environmental contamination were made during the

last quarter of the 20th century. During that period, countries from all over the

world, inter-governmental agencies and many non-governmental organizations

(NGOs) participated in well-known international meetings in order to determine

the theoretical and practical considerations of the new established idea of

sustainability. More specifically, in 1972 the United Nations organized the

Conference on Human Environment in Stockholm, where the participants agreed

on a joint Declaration containing 26 principles for the environment and the

development, an action plan with 109 recommendations and a Resolution. The

issue of sustainable development was the focal point in the 48th Plenary of the

General Assembly in 1982, the International Union for the Conservation of

Natural Resources (IUCN) in 1984 and the World Commission on Environment

Development (WCED) in 1987. Indeed, the turning point for the establishment

of sustainable development took place in Rio de Janeiro in 1992 during the

United Nations Conference on Environment Development (UNCED). The

highlight of that conference was the adaption of “Agenda 21: “a program of


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action for sustainable development” that was composed by 40 chapters separated

into four main sections: Social and Economic Dimensions, Conservation and

Management Resources for Development, Strengthening the Role of Major

Groups and Means of Implementation. A decade after the Rio declaration, the

World Summit on sustainable development was held in Johannesburg in order to

renew global commitment to the idea of sustainability. The achievement and

further improvement of sustainability is an ongoing course and for that reason

many international conferences, such as the Earth Summit held in Brazil in June

2012 happen on a regular basis.

Over time, the notion of sustainable development has not only changed but also

evolved. According to the definition by the Brundtland Commission on Our

Common Future, sustainable development is mentioned as “Development which

meets the needs of the present without compromising the ability of future

generations to meet their own needs”4. Another well-known definition of

sustainable development was established in Rio de Janeiro during the UNCED:

“The right to development must be fulfilled so as to equitably meet

developmental and environmental needs of present and future generations”5.

According to the European Commission, sustainable development stands for

“meeting the needs of present generations without jeopardizing the ability of

future generations to meet their own needs – in other words, a better quality of

life for everyone, now and for generations to come”6. Despite the differences in

the above definitions, common place constitutes the issues of growth,

environmental protection, prosperity and equality.

The European Union (EU) poses increased emphasis on sustainability and in that

direction the European Commission determines three basic pillars: economic

efficiency, social cohesion and environmental protection. Taking into account

the current financial crisis in the EU and its negative effects on employment,

growth and poverty, the issue of sustainable development is of particular interest.

Under the auspices of the EU certain strategies and action plans on sustainable

consumption and production, sustainable cities and sustainable use of natural

resources have been developed. However, there are unsustainable trends that

have to be eliminated, while priority should be given to efforts made in the areas

of climate change, transportation, biodiversity and natural resources.

The overarching objective of the present paper is to investigate the linkage

between sustainable development and economic growth in the Eurozone

4Report of the World Commission on Environment and Development, 1987. 5Report of the United Nations Conference on Environment and Development, 1992. 6http://ec.europa.eu/environment/eussd/


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countries. For that reason, we employ certain sustainable development indicators

with the intention of identifying the critical indicators that particularly contribute

to the GDP growth rate. Furthermore, we seek to highlight the differences among

the Eurozone countries as far as the significance of each indicator is concerned.

Based on alternative econometric models we seek to draw concrete conclusions

for policy making so as to achieve high growth levels in the context of

sustainability. The analysis of our paper focuses on the Eurozone due to the wide

range of diversity of GDP growth rates among its countries despite the existence

of a common monetary policy. Additionally, the recent financial crisis in the

examined area raises further considerations for the policies that should be

undertaken in order to abolish the imperfections of a common currency

spotlighting the issue of sustainability.

Specifically, this paper is structured as follows: Section 2 analyzes the results of

the previous research work in the field of sustainable development. Section 3

elaborates on the data under examination and analyzes the applied methodology.

Section 4 presents the impact of sustainable development indicators on GDP

growth rate for the selected Eurozone countries. Finally, Section 5 discusses the

conclusions of the paper and suggests ideas for further research.

Literature review

The concept of sustainable development constitutes a particularly favorable

research field among academics, researchers, government authorities and

international organizations. Sustainable development is a relatively recent issue

considering that it emerged in the last quarter of the 20th century, forming new

grounds for improvements in standards of living. Indeed, it has a global

perspective and sets new horizons for an alternative growth paradigm. In that

frame, we could divide the available research work into two broad categories; the

studies of the first category analyze the theoretical framework of sustainability,

while the remaining studies apply statistical procedures in order to identify the

linkages between sustainable development and social prosperity.

Taking into account the former, we observe alternative theoretical considerations

of the examined issue of sustainability. For instance, Jeroen and Hofkes (1997)

investigate different approaches of economic modeling of sustainable

development such as neoclassical growth models, disaggregated models,

integrated and co-evolutionary models Szabó (2011) refers to the evolution of

sustainable development which contributes to the continuous improvement of

life through the rational and efficient use of resources. Another important study

has been performed by Banerjee (2003) analyzing the contradictions of the

notion of sustainable development. The author explores the consequences of


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sustainable development in the Third World, making particular reference to

biodiversity, biotechnology and intellectual property rights. Additionally,

Anagnoste and Agoston (2009) discuss the main causes of the current economic

crisis and make proposals for possible solutions from the standpoint of

sustainability. The relationship between the Lisbon agenda and the strategy of

sustainable development adopted by the European Council is analyzed as well.

In that line, the guiding principles of sustainable development that the EU has

adopted are based on the revised Lisbon Agenda regarding economic growth and

the creation of new jobs.

Sustainable development constitutes a general philosophy and in order to be

assessed several indicators have been developed. Bossel (1999) defines the

notion of sustainable development and the corresponding indicators of

sustainability to facilitate the implications of sustainability with a matching set of

indicators. Tasaki et al. (2010) identify 1,790 indicators of sustainability which

are classified into 77 sub-categories and eventually into four headline categories.

They also suggest a majority of tasks as far as the future development of these

indicators is concerned. In particular, they suggest the creation of time-conscious

indicators, the measurement of interactions between elements of a system, the

confrontation of transboundary issues, the evaluation of quality and the

revelation of the relationship between everyday life and sustainable

development. Similarly, Tanguay et al. (2009) assess 17 studies evaluating the

use of sustainable development indicators in an urban setting. Through this

analysis a lack of consensus on the conceptual framework and on the selection

and the optimal number of indicators is seen. Finally, several classifications of

sustainable development indicators are given in order to acknowledge the

problems that are caused by territorial practices.

A publication from the United Nations in 20077 presents the guidelines and

methodologies of sustainable development indicators according to Agenda 21

and the Johannesburg Plan of Implementation. The outcome contains 96

indicators analyzing the methodology for each one. Also, it provides guidance on

the way that national indicators of sustainability should be developed in order to

better comprehend the various dimensions of the concept of sustainable

development and their complex interactions.

Considering the empirical examination of sustainable development there is a

limited number of research papers, considerably less than those that adopt a

theoretical standpoint. In that framework, Rennings and Wiggering (1997)

recommend that sustainable development and its indicators could be separated

7Indicators of Sustainable Development: Guidelines and Methodologies, 2007.


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into two categories, the weak and the strong. Weak sustainability is based

particularly on neoclassical theory and strong sustainability that does not accept

the degree of substitution that weak sustainability assumes. Böhringer and

Lӧschel(2004) refer to computable general equilibrium models as a

methodological tool which is suitable for measuring the influences of policy

interference on three dimensions of sustainable development, such as

environmental quality, economic performance and equity. Important sustainable

development indicators can be integrated into computable general equilibrium

models allowing in that way further analysis.

Ziolkowska and Ziolkowski (2010) analyze the sustainable development strategy

of the European Union that is currently being adjusted and updated to new

ecological, economic and social challenges. They also provide suggestions for

the future emphasizing the necessity for a more extensive discussion on a

number of issues regarding sustainable development, mainly on ‘Good

Governance’. A similar approach has been made by Chistilin (2010), who

formulates the fundamental principles of sustainable development as well as the

basic equation of development. More specifically, the fundamental principles of

sustainable development that the author expresses are the principle of minimum

resource dissipation, the equation of self-organization and the law of conserving

the economic potential of a social system. Furthermore, Costantini and

Monni(2005) through their research work manage to find ways to design certain

policy actions and to measure performance and results. Their goal is to identify a

numerical measure of “sustainable human development” by enhancing the issue

of human development with certain environmental aspects in the area of the

European Union. Last but not least, Adelle and Pallemaerts(2009) construct a set

of sustainable development indicators after a review of 40 research projects

regarding the progress of sustainable development indicators. They also

recommend rethinking and restructuring the landscape of sustainable

development indicators in some areas, such as the governmental area as the

organization of the existing indicators is highly contestable.

The European Commission examines regularly8 the progress of the EU towards

the implementation of sustainable development. Considering the last monitoring

report published in 2011, the results of the examined indicators are mixed; some

indicators reveal significant progress while the majority demonstrates

unfavorable conditions. In addition, the emergence of the economic and financial

crisis further complicates the situation, since it severely affects many of the

relevant indicators. The EU faces a critical challenge; the existing growth model

8 Every two years Eurostat publishes a report regarding the progress towards the objectives of the EU Sustainable Development Strategy.


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proved to be insufficient and should be amended if the current crisis is to be

overcome. At the same time, environmental waste has reached dangerous

proportions and is on the verge of causing catastrophic damage to the

environment thus there is no room for concession. Indeed, sustainable

development provides a particular opportunity for growth and environmental

planning.

Data and Methodology

Data

Taking into account that we intend to investigate the relationship between

growth and sustainability, we consider GDP annual growth as the dependent

variable. We analyze data from 2000 to 2009 for 16 countries of the Euro zone,

particularly referring to Belgium, Germany, Ireland, Greece, Spain, France, Italy,

Luxemburg, Estonia, Malta, the Netherlands, Austria, Portugal, Slovenia,

Slovakia and Finland. Table 1 records the GDP growth rate for the selected

countries from 2000 to 2009.

Table 1: GDP growth rate (annual) of Eurozone countries (%)

Country

Year

200

0

200

1

200

2

200

3

200

4

200

5

200

6

200

7

200

8

200

9

Austria 3,7 0,9 1,7 0,9 2,6 2,4 3,7 3,7 1,4 -3,8

Belgium 3,7 0,8 1,4 0,8 3,3 1,7 2,7 2,9 1,0 -2,8

Finland 5,3 2,3 1,8 2,0 4,1 2,9 4,4 5,3 0,3 -8,4

France 3,7 1,8 0,9 0,9 2,5 1,8 2,5 2,3 -0,1 -2,7

Germany 3,1 1,5 0,0 -0,4 1,2 0,7 3,7 3,3 1,1 -5,1

Greece 4,5 4,2 3,4 5,9 4,4 2,3 5,5 3,0 -0,2 -3,3

Estonia 9,6 8,5 7,9 7,6 7,2 9,4 10,6 6,9 -5,1 -13,9

Italy 3,7 1,9 0,5 0,0 1,7 0,9 2,2 1,7 -1,2 -5,1

Luxembourg 8,4 2,5 4,1 1,5 4,4 5,4 5,0 6,6 0,8 -5,3

Malta 5,0 -1,6 2,6 -0,3 0,9 4,0 1,9 4,6 5,4 -3,3

Portugal 3,9 2,0 0,8 -0,9 1,6 0,8 1,4 2,4 0,0 -2,9

Slovakia 1,4 3,5 4,6 4,8 5,1 6,7 8,3 10,5 5,9 -4,9

Slovenia 4,3 2,9 3,8 2,9 4,4 4,0 5,8 6,9 3,6 -8,0

Ireland 9,2 4,8 5,9 4,2 4,5 5,3 5,3 5,2 -3,0 -7,0


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Netherlands 3,9 1,9 0,1 0,3 2,2 2,0 3,4 3,9 1,8 -3,5

Spain 5,0 3,6 2,7 3,1 3,3 3,6 4,0 3,6 0,9 -3,7

Source:http://www.worldbank.org/

Selection criteria for sustainable development indicators

Considering that the fundamental purpose of our research is to assess the

relationship between economic growth and sustainability, we should select a

representative and reliable set of sustainable development indicators. Indeed,

there is not a general consensus among the researchers as far as the defined set of

sustainable indicators is concerned. International organizations and empirical and

meta-analytic studies present an array of alternative sustainable development

indicators, while in many cases the suggested indicators are hundreds. What is

more, in almost all the published research work the need for a defined conceptual

framework of sustainability and the determination of an optimal set of

representative indicators are noted. Taking into account that we focus on the

Euro zone countries, we opt to follow the guidance and methodology of the

European Commission. Although many authors assess the theoretical basis and

methodological background of the indicators and classification followed by the

European Commission, our study is the first attempt to link the suggested

indicators with growth rates through the application of an econometric analysis.

In fact, there are more than a hundred sustainable indicators held by the

European Commission; however, eleven of them are defined as headline

indicators. The European Commission separates indicators of sustainable

development into nine basic categories: Socio-economic development,

Sustainable consumption and production, Social inclusion, Demographic

changes, Public health, Climate change and energy, Sustainable transport,

Natural resources and Global Partnership. Therefore, each headline indicator is

considered as the most representative of its category. Our study examines eight

out of the eleven headline indicators due to data limitations. The selected

indicators are Growth rate of real GDP per capita, Resource productivity,

Official development assistance as a share of gross national income (GNI),

Employment rate of older workers total females and males, Life expectancy at

birth by sex, Greenhouse gas emissions, Total renewable electricity net

generation and Energy consumption by transport mode and related to GDP. The

three indicators on which there was no sufficient data and which were thus

excluded from our analysis are People at risk of poverty, Common bird index

and Fish catches taken from stocks outside safe biological limits. In order to

facilitate the analysis of results we classify the above indicators into three


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groups; the first group refers to economic indicators, the second includes social

indicators while the third consists of environmental indicators. Table 2 depicts

the categorization of the selected eight indicators.

Table 2. Classification of headline indicators of sustainability

Economic

Indicators

a. Growth rate of real GDP per capita in PPS

b. Resource productivity (ratio of GDP divided by

domestic material consumption)

c. Official development assistance as a share of gross

national income (GNI)

Social Indicators

a. Employment rate of older workers total females and

males (age group 55-64, as a share of total

population of the same age group)

b. Life expectancy at birth (females and males)

Environmental

Indicators

a. Greenhouse gas emissions(base year 1990, the sin

greenhouse gases used are weighted by their global

warming potentials)

b. Total renewable electricity net generation (in BTU,

it measures the total production of electricity which

comes from renewable sources)9

c. Energy consumption by transport mode and related

to GDP (finally energy consumption of transport,

road rail, inland navigation and aviation, in toe)

9The European Commission uses a relevant indicator named “Share of renewable energy

in gross final consumption” but its data did not satisfy all the requirements of our sample. As a result, we employed “Total renewable electricity net generation”. Source: www.eia.gov.


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Research methodology

Considering that the data set consists of cross sectional units that are surveyed

over time we employ a panel data analysis in order to enrich our empirical

findings. Specifically, the data represent a balanced panel, since each county in

the sample has nine (9) observations. In general, the techniques of panel, by

combining time series of cross section observations, provide more informative

data, less collinearity among variables, more degrees of freedom and more

efficiency. Furthermore, panel data analysis provides benefits in terms of

stationarity. In particular, panel data unit root tests increase the power of usual

unit root tests based on individual time series (Augmented Dickey-Fuller,

Phillips-Perron etc.). In the present study Levin-Lin (Levin and Lin, 1992) panel

data unit root test is performed with the intention to test the stationarity of the

examined series. Last but not least, panel can take into account the countries’

heterogeneity allowing for explicit comparisons between the examined Eurozone

countries.

Our estimations generally rely on the following panel data regression model:

Variable Y represents the dependent variable, specifically GDP growth rate. The

independent variables represent the indicators of sustainable development. Table

3 describes the exact meaning of the symbols used.

1 2 3 4

5 6 7 8 9

.

it i i it i it i it i it

i it i it i it i it i it it

Y a b real gdp b respro b oda b emplrate

b lef b lem b gasem b renew b transp ε

= + + + + +

+ + + + +

(model 1)


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Table 3: Abbreviations of the independent variables

We employ three models in order to estimate the effect of sustainable

development indicators on GDP growth rate. Model 1 and Model 2 rely on the

following equation:

In Model 1 time and individuals are not taken into consideration since a pooled

least square regression is employed. Therefore, the constant term and all the

independent variables are considered to have common coefficients. In Model 2, a

pooled least square regression is also employed, however this estimation omits

the effects of sustainable development indicators on GDP growth rate that were

not found to be statistically significant by Model 1 estimation. The non-

statistically significant characteristic emerges from the fact that the p-value of

these indicators is less than 5%. The omitted indicators are “Life expectancy of

males”, “Life expectancy of females” as well as “Official development

assistance”. In other words, Model 2 has exactly the same characteristics as

Abbreviation Explanation

real.gdp Growth rate of real GDP per capita in PPS

respro Resource productivity

oda Official development assistance as a share of gross national

income (GNI)

emplrate Employment rate of older workers (total females and males):

age group 55-64

lef

lem

Life expectancy at birth (females)

Life expectancy at birth (males)

gasem Greenhouse gas emissions (base year 1990)

renew Total renewable electricity net generation (in BTU)

transp Energy consumption by transport mode and related to GDP

1 2 3 4

5 6 7 8 9

.

it it it it it

it it it it it it

Y a b real gdp b respro b oda b emplrate

b lef b lem b gasem b renew b transp ε

= + + + + +

+ + + + +

(Model 2)


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Model 1, without taking into account the non-statistically independent variables

that existed in Model 1.

Model 2 provides a general idea regarding the linkages between sustainable

development and GDP growth rate in the Eurozone countries. The findings of the

analysis are particularly useful for the examined countries as a whole,

considering that our sample represents a Union with common strategies and

policies up to a certain level. However, each country has different social and

economic characteristics, while the issue of sustainability has not been developed

equally everywhere. For that reason, we perform another Model (Model 3) in

order to examine the effect of each indicator in the selected countries separately.

We believe that apart from policies on the EU level, each country should develop

its own course of action. Model 3 relies on the following equation:

In Model 3 a least square dummy variable estimation (LSDV) is performed,

allowing for individual fixed effects and variant slope coefficients across cross

sections. The fixed effect method is considered appropriate since the cross

sectional units of the selected sample compose a closed sample (Eurozone

countries) and are not random drawings from a larger one (Gujarati, 2004). In

this way, the different influence of independent variables on each country’s GDP

is investigated. In order to specify this model we were forced to drop two

independent variables which are “Official development assistance” and “Total

renewable electricity net generation”. This wastage was the direct result of

statistical software limitations.

The above analysis assayed the selection of data used in our sample and clarified

the components on which the separation of the models was made. Moreover, the

methodology used is briefly analyzed. Subsequently, there is an immediate need

to conclude into the preferable model in order to make our final estimation. In

the Section that follows, a brief description of the preferred model will be made

and further justification for the models rejected will be given.

1 2 3

4 5 6 7

.

it i i it i it i it

i it i it i it i it it

Y a b real gdp b respro b emplrate

b lef b lem b gasem b transp ε

= + + + +

+ + + + (Model 3)


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Empirical Results

In this section initially are exhibited the Levin-Lin (LL) panel data unit root

test’s results (Table 4), while the following paragraphs present the empirical

results of the econometric analysis regarding the influence of sustainable

development indicators on GDP growth rate.

Table 4: Levin-Lin Unit Root Test

Series LL-statistic Prob. Unit Root

Y 9.50 1.00 Yes

real.gdp 9.76 1.00 Yes

respro -1.79 0.03 No

oda -10.11 0.00 No

emplrate -5.88 0.00 No

lef -6.34 0.00 No

lem -10.06 0.00 No

gasem 4.58 1.00 Yes

renew -9.14 0.00 No

transp -4.26 0.00 No

The Levin-Lin test indicates the presence of unit root in “GDP growth rate”,

“Growth rate of real GDP per Capita in PPS” and “Greenhouse gas emissions”.

The test fails to reject the null hypothesis of unit root in 5% significance level.

Contrarily, in case of the other examined series we find strong evidence of

stationarity (no unit root). The fact that there are non-stationary variables in our

models and indeed the dependent variable “GDP growth rate” may affect the

validity of the estimations. However, the empirical evidence implies that GDP

growth rates especially in the case of developed countries exhibit low volatility

and mean reverting behavior. As a matter of fact, we could consider that the

observed non-stationarity does not reduce the estimations’ robustness.

The Eurozone as one country

Our first step was to run a simple pooled regression without taking into account

individual and time dimensions. In that model the countries of our sample are

essentially being treated as one. According to the estimated results of Model 1

three independent variables, namely “Gas emission”, “Official development

assistance” and “Life expectancy of males”, are not statistically significant as

their p-value is more than 0.05. The rest of the independent variables are


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statistically significant and each of them has a positive effect on GDP growth

rate. Unique exception constitutes “Total renewable electricity net generation”

which is negatively associated with GDP growth rate.

Table 5. Model 1 estimation

Dependent Variable: GDP growth rate

Independent Variable

Coefficient

Std. Error

t-Statistic

Prob.

Constant term 6.21 4.39 1.41 0.16

Employment rate of older workers 0.04 0.01 3.29 0.00

Resource productivity 0.44 0.10 4.36 0.00

Gas emissions 0.01 0.01 1.33 0.19

Energy consumption by transport mode 0.02 0.00 4.72 0.00

Real GDP 1.01 0.01 100.03 0.00

Total renewable electricity net generation -1.12 0.47 -2.40 0.02

Official development assistance 0.35 0.40 0.87 0.39

Life expectancy males 0.11 0.09 1.26 0.21

Life expectancy females -0.23 0.10 -2.20 0.03

Regression Statistics

R-squared 0.99

Adjusted R-squared 0.99

F-statistic 716.98

Prob(F-statistic) 0.00

Durbin-Watson stat 1.02

Log likelihood -5.53

Schwarz criterion 0.96

Considering the statistics of the performed equation, we observe satisfactorily

high R-squared and Adjusted R-squared values (0.99). In addition, the value of

the Durbin-Watson statistic could be considered adequate (1.02), indicating low

probability of autocorrelation in the data.


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In the estimation of Model 2 (Table 5) we drop the 3 insignificant independent

variables of model 1 in order to improve the fitness of our model. In fact, all the

independent variables are statistically significant apart from “Total renewable

electricity net generation” which could be characterized as weakly statistical

significant since its p-value is 0.06. In that estimation every independent variable

has positive influence on GDP growth rate excepting “Total renewable electricity

net generation” which negatively affects GDP growth, as observed in Model 1.




Coefficient

Std. Error

t-Statistic

Prob.

Constant term -3.22 0.66 -4.89 0.00

Employment rate of older workers 0.02 0.01 2.86 0.00

Resource productivity 0.40 0.10 3.96 0.00

Gas emissions 0.01 0.01 2.29 0.02

Energy consumption by transport mode 0.01 0.00 3.59 0.00

Real GDP 1.00 0.01 109.47 0.00

Total renewable electricity net generation -0.83 0.45 -1.84 0.07


R-squared 0.99


F-statistic 870.81



Log likelihood -17.56


Taking into account that both Models have been estimated with the same

method, we compare them in order to select the most reliable. For that reason we

compare the values of the Log likelihood statistic and the Schwarz information

criterion, preferring the model with the higher value of the former and the lower

value of the latter. Considering the Log Likelihood of Models 1 and 2 we


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conclude that the second model has higher absolute value (17.56 versus 5.53)

and thus it can be considered as the best choice. Likewise, the Schwarz criterion

of Model 1 (0.95) is higher than that of Model 2 (0.92) and as a result Model 2

prevails against Model 1. In addition, the value of the Durbin-Watson statistic

should be approximately 2 in order to avoid any sign of autocorrelation in the

sample. Model 2 also satisfies this condition as its Durbin-Watson statistic is

1.42, while Model 1 has a corresponding value of 1.019. Therefore, taking into

consideration all the above analysis Model 2 outperforms Model 1.

The empirical results of the prevailing model demonstrate the statistical

significance of certain indicators to GDP growth rate, which are “Employment

rate of older workers”, “Resource productivity”, “Gas emissions”, “Energy

consumption by transport mode”, “Real GDP” and “Total renewable electricity

net generation”. Indeed, “Real GDP”, “Resource productivity” and “Total

renewable electricity net generation” present the highest coefficients, while the

other three show negligible coefficients. This observation renders apparent the

need for further improvements on “Resource productivity” through the

minimization of the raw materials directly used by the Eurozone countries. An

interesting finding derives from the negative sign of the “Total renewable

electricity net generation” indicator, suggesting a dramatic weakness in the

European economy to incorporate alternative sources of electricity into its

production processes. Thus, the first step that should be taken by the European

authorities is to alter the industrialized model as far as the use of electricity is

concerned; stating alternatively, the coefficient of the examined indicator should

be changed into positive.

The Eurozone countries separately

The above Models intend to investigate the relationship between growth and

sustainability on the Eurozone level. Model 3 assesses the effects of sustainable

development indicators on GDP growth rate of each Eurozone country. The

applied Model is characterized by fixed effects, the intercept is assumed to be

constant, while the slope coefficients vary among the countries of our sample.

The idea for this model is to examine possible differences between each

explanatory variable and GDP growth rate at country level. Considering the

empirical results, we observe significant divergences among the coefficients of

the independent variables, while not all the indicators of sustainable development

are found to be statistically significant. For that reason, Table 7 presents the main

findings derived from our econometric analysis. Particularly, we demonstrate the

most important indicators for each Eurozone country separately.


31




Coefficient

Std. Error

t-Statistic

Prob.

Constant term -4.15 10.60 -0.39 0.70

Employment rate of older workers

Greece 0.15 0.08 1.92 0.06

Malta 0.28 0.12 2.45 0.02

Slovenia 0.10 0.06 1.75 0.09

Resource productivity

Greece 6.55 2.40 2.73 0.01

Spain -4.62 2.53 -1.83 0.08

Malta 0.65 0.11 5.73 0.00

Gas Emissions

Ireland 0.08 0.05 1.72 0.10

Malta -0.10 0.02 -4.50 0.00

Energy consumption by transport mode

Malta 0.04 0.01 4.89 0.00

Real GDP

Belgium 0.95 0.11 8.91 0.00

Germany 1.02 0.05 19.28 0.00

Ireland 1.09 0.04 27.04 0.00

Greece 0.93 0.04 23.33 0.00

Spain 0.91 0.07 12.92 0.00

France 1.02 0.11 9.66 0.00

Italy 0.91 0.14 6.38 0.00

Luxembourg 1.05 0.04 25.64 0.00

Estonia 0.99 0.06 15.27 0.00

Malta 1.24 0.03 35.86 0.00

Netherlands 0.82 0.17 4.84 0.00

Austria 0.99 0.06 17.69 0.00

Portugal 0.97 0.04 23.35 0.00

Slovenia 0.94 0.06 14.90 0.00

Slovakia 0.99 0.03 28.84 0.00

Finland 1.00 0.05 19.08 0.00

Life expectancy females Greece -2.17 1.15 -1.89 0.07


32


R-squared 0.99


F-statistic 438.61


Log likelihood 199.29



Taking into account the data of Tables 6 and 7 above, we observe that Models 2

and 3 demonstrate almost the same sustainable development indicators with

statistical significance, while the indicator “Real GDP” has a similar coefficient

very close to one in all the Eurozone countries. The only difference is the

appearance of “Total renewable electricity net generation” in the former and

“Life expectancy females” in the latter. As far as Model 3 is concerned, the

indicators “Employment rate of older workers”, “Resource productivity” and

“Gas emissions” display particular diverging coefficients. In particular, the first

one has a positive effect on GDP growth rate in Greece, Malta and Slovenia;

nevertheless, in Malta its significance is almost triple (0.28) relative to Slovenia

(0.1), while in Greece it is moderate (0.15). “Resource productivity” is, in fact,

the most controversial indicator, since it deviates from -4.62 in Spain to 6.55 in

Greece; in Malta the relative coefficient is slightly greater than zero (0.65). The

indicator “Gas emissions” has remarkably low coefficients in Ireland and Malta,

while the coefficients display different signs (0.08 and -0.1 respectively).

Finally, the coefficients of “Energy consumption by transport mode” and “Life

expectancy females” proved to be statistically significant in Malta (0.04) and

Greece (-2.17) respectively.

Discussion of results

Interestingly, the sustainable development indicators have particular significance

in countries such as Greece, Ireland and Spain, which are the core economies of

the current European financial crisis. Indeed, the first two countries received a

joint bailout program from the IMF, EU and ECB, while the Spanish banking

system was injected with €100 billion in loans due to macroeconomic

difficulties. Moreover, neither country with macroeconomic stability from

central and northern Europe appears to be affected by any indicator of


33

sustainability. Indeed, the Eurozone countries in severe economic crisis should

concede sustainable development as an opportunity through which they could

improve their economic environment.

Although certain indicators proved to be statistically significant in a set of

Eurozone countries, the variation among the coefficients demonstrates the need

for different policies and initiatives that should be applied on a national level. In

some cases, the tightening of regulatory framework could generate outcomes in

the opposite direction; what is considered necessary, is an overall action plan of

sustainable development based on the particular social, economic and

environmental characteristics of each country.

The last two observations render clear the need for the Eurozone countries to

move towards political and economic integration. The adaption of a single

currency without solid political and monetary foundations is not enough for

economic growth and social prosperity. In that frame, sustainable development

should be cultivated and further incorporated centrally in the Eurozone. At the

same time, the demographic, legal, economic and climatic conditions of each

geographic area or country should be taken into account. To a certain extent, the

applied policies should be harmonized with the local potentials and

characteristics. The recent debt crisis that is still evolving demonstrates the

necessity for a new European perspective where the ultimate objectives should

be the elimination of poverty, further technological development and

environmental sanitation.

Conclusions and suggestions for further research

The economic model of the last decades introduced significant improvements to

the standard of living. The economies have become more open, international

trade and capital flows increased dramatically, employee and capital mobility

were facilitated under the ever-increasing concept of globalization. However,

that economic growth caused severe consequences to the environment and the

natural resources, since in the name of prosperity humans undermined the effects

of the established economic development model. During the last quarter of the

20th century, environmental concerns began to grow and a new idea of parallel

economic growth and environmental protection emerged. Sustainable

development formed the grounds for a paradigm shift, where further economic

growth could be achieved through environmental sanitation.

The present study focuses on the linkages between GDP growth rate and

sustainable development in an area of particular significance such as the


34

Eurozone. The concept of sustainability constitutes a controversial topic through

which quantitative measures should be expressed; thus, we analyze a set of

sustainable development indicators held by the European Commission. Our

study constitutes an inventive attempt in the literature, since we intend to identify

the critical parameters of sustainability that affect the economic growth in the

Eurozone and in each country separately applying alternative econometric

models. We attempt to draw reliable conclusions that could be the basis for

policy making in the Eurozone. At the same time, we determine certain action

plans that should be applied in particular countries due to specific economic

conditions.

From the eleven examined indicators of sustainability, only seven of them

proved to be statistically significant. The two models that assess the Eurozone as

one country and the Eurozone countries separately show consensus on

“Employment rate of older workers”, “Resource productivity”, “Real GDP”,

“Energy consumption by transport mode” and “Gas emissions”. “Total

renewable electricity net generation” and “Life expectancy females” present

statistical significance in the Eurozone and in Greece respectively. Examining

GDP growth rate and sustainable development in the Eurozone, we could argue

that “Resource productivity” and “Total renewable electricity net generation”

present the highest coefficients and, thus, should be considered with greater

interest. Indeed, the negative sign of the last indicator together with the positive

sign of “Gas emissions” and “Energy consumption by transport mode”

demonstrate the distortions of the current economic model. This fact highlights

the necessity for an overall alteration of the economic development

fundamentals. Along this line, rigid legislative arrangements would prove

meaningless. At country level, the significant deviations of the coefficients

reveal the specific opportunities and weakness of each country based on the

different socioeconomic frameworks. Interestingly, countries experiencing the

current economic crisis could boost their growth rate through sustainable

development.

The conclusions of the present paper could be the starting point for further

research in the field of sustainable development and growth. Initially, apart from

the selected set of indicators, the issue of sustainability in the Eurozone could be

examined with alternative measures available in the literature. That procedure

may reveal other areas of particular importance, where policy makers should

focus. In addition, similar empirical studies could be performed in other

developed and emerging economies in order to identify the linkages between

sustainability and growth. The findings from these areas may reveal aspects of

successful action plans as well as policies with limited efficiency. Considering

the growing environmental considerations in the light of the current economic


35

crisis in the Eurozone, the issue of sustainable development is expected to be at

the centre of interest in the following years.

References

Adelle., C. and Pallemaerts., M., 2009, Sustainable Development Indicators, An

Overview of relevant Framework Programme funded research and

identification of further needs in view of EU and international activities.

Brussels: European Commission.

Anagnoste, S. and Agoston, S., 2009, Sustainable Development in Global

Economy, Annals of Faculty of Economics 2 (1): 230-235.

Bartik, T., 1995, Economic Development Strategies (Upjohn Institute Working

Paper, No. 95-33), Kalamazoo, MI: W.E. Upjohn Institute for

Employment Research. Retrieved April 10, 2012, from:

http://research.upjohn.org/up_workingpapers/33

Böhringer, C. and Löschel, A., 2004, Measuring Sustainable Development: The

Use of Computable General Equilibrium Models. ZEW Discussion

Papers, No. 04-14.

Bossel, B., 1999, Indicators for Sustainable Development: Theory, Method,

Applications, A Report to the Balaton Group. Canada: International

Institute for Sustainable Development.

Banerjee, S., 2003, Who Sustains Whose Development? Sustainable

Development and the Reinvention of Nature, Organization Studies 24

(1): 143–180.

Briassoulis, H., 2001, Sustainable Development and its Indicators: Through a

(Planner's) Glass Darkly, Journal of Environmental Planning and

Management, 44 (3): 409-427.

Chistilin, D., 2010, Sustainable Economic Development: The Main Principles

and the Basic Equation, Romanian Journal of Economics 30: 95-109.

Costantini., V. and Monni., S., 2005, Sustainable Human Development for

European Countries, Journal of Human Development 6 (3): 329-351.

Dhamija, N., 2008, Economy news. Retrieved April 10, 2012, from

http://www.economynews.in/kb/2008-11-

21/Key_Indicators_for_Economic_Growth_2103.html

Energy Information Administration. International Energy Statistics.

Retrieved April 2, 2012,

http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=6&pid=29&a

id=12&cid=r3,&syid=2000&eyid=2010&unit=QBTU

Eurofound., 2009, EurLIFE- At risk of poverty rate. Retrieved March 12, 2012,

http://www.eurofound.europa.eu/areas/qualityoflife/eurlife/index.php?te

mplate=3&radioindic=181&idDomain=3


36

European Commission., 2011, Economic forecasts. Retrieved March 21, 2012,

http://ec.europa.eu/economy_finance/eu/forecasts/2011_spring_forecast

_en.htm

European Commission, 2011, Sustainable development in the European Union,

2011 monitoring report of the EU sustainable development strategy.

Luxemburg: Publications Office of the European Union.

European Commission., 2010, Health Expectancy. Retrieved March 10, 2012,

http://ec.europa.eu/health/indicators/echi/list/echi_40.html#main?Keep

This=true&TB_iframe=true&height=450&width=920

Eurostat.(2012). Sustainable Development Indicators. Retrieved March 30, 2012,

from: http://epp.eurostat.ec.europa.eu/portal/page/portal/sdi/indicators

Montenegro, A., 2004, An Economic Development Index. Econ WPA

Working Paper, Development and Comp Systems Series, No. 0404010.

Retrieved April 10, 2012,

http://ideas.repec.org/p/wpa/wuwpdc/0404010.html

Garland, N., Hadfield, M., Howarth, G. and Middleton, D., 2009, Investment in

Sustainable Development: A UK Perspective on the Business and

Academic Challenges, Sustainability, 1: 1144-1160.

Grossman, G. and Krueger, A., 1995, Economic Growth and the Environment,

The Quarterly Journal of Economics, 110 (2): 353-377.

Kelley, A., 1991, The Human Development Index: Handle with Care, Population

and Development Review, 17 (2): 315-324.

Lele, S., 1991, Sustainable development: A critical Review, World Development,

19 (6): 607-621.

McGranahan, D., 1972, Development indicators and development models,

Journal of Development Studies, 8 (3): 91-102.

Nafziger, E. W., 2012. Economic Development, New York: Cambridge

University Press.

OECD iLibrary, 2012, Official Development assistance. Retrieved March 30,

2012, http://www.oecd-ilibrary.org/sites/factbook-2011-

en/11/04/03/index.html;jsessionid=4em91qjenisnu.delta?contentType=/

ns/StatisticalPublication,/ns/Chapter&itemId=/content/chapter/factbook

-2011-101-

en&containerItemId=/content/serial/18147364&accessItemIds=&

Opschoor, H. and Reijnders, L., 1991, Towards sustainable development

indicators, In Kuik, O. and Verbruggen, H., In Search of Indicators of

Sustainable Development, Kluwer Academic Publishers: 7-27.

Pozo, S., Sánchez-Fung, J., Santos-Paulino, A., 2010, Economic Development

Strategies in the Dominican Republic. World Institute for Development

Economics Research (UNU-WIDER), No. 115.


37

Rennings, K. and Wiggering, H., 1997, Steps towards indicators of sustainable

development: Linking economic and ecological concepts, Ecological

economics 20: 25-36.

Shafik, N., 1994, Economic Development and Environmental Quality: An

Econometric Analysis, Oxford Economic Papers, l (46): 757-773.

Szabo, Z., 2011, Analysis of research on sustainable development: The goals of

sustainable development, practical and theoretical framework in EU and

Romania, The Juridical Current 47: 253-262.

Tasaki, T., Kameyama, Y., Hashimoto, S., Moriguchi, Y. and Harasawa, H.,

2010, A survey of national sustainable development indicators, Int. J.

Sustainable Development 13 (4): 337–361.

Tanguay, G., Rajaonson, J., Lefebvre, J., Lanoie, P. (2009) Measuring the

Sustainability of Cities: A Survey-Based Analysis of the Use of Local

Indicators. Cirano – Scientific Publications.

United Nations Conference on Environment and Development., 1992,

Programme of Action for Sustainable Development. Agenda 21. Rio de

Janeiro.

United Nations, 2007, Indicators of Sustainable Development: Guidelines and

Methodologies. 3rd

ed. New York: United Nations. United Nations

Econimic Commission for Europe, Statistical Database. People at risk

of poverty. Retrieved March 30, 2012,

http://w3.unece.org/pxweb/search/?SearchString=people+at+risk+of+po

verty&pageNumber=0&lang=1

Van den Bergh, J. and Hofkes, M., 1997, A Survey of Economic Modelling of

Sustainable Development. Tinbergen Institute Discussion Papers, 107

(3).

World Commission on Environment and Development., 1987, Our Common

Future. New York: Oxford University PressWorld Data Bank. World

Development Indicators & Global Development Finance. Retrieved

April 17, 2012,

http://databank.worldbank.org/ddp/home.do?Step=2&id=4&hActiveDi

mensionId=WDI_Series

World Resources Institute. Climate, Energy and Transport. Retrieved March 12,

2012, http://www.wri.org/publications/climate

Ziolkowska, J. and Ziolkowski, B., 2010, Sustainable Development in the

European Union: Tools for policy evaluation, Annals of the University

of Petroşani, Economics, 10 (3): 373-382.

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